No abstract

It is clear that discards from commercial fisheries are a key food resource for many seabird species around the world. But predicting the response of seabird communities to changes in discard rates is problematic and requires historical data to elucidate the confounding effects of other, more 'natural' ecological processes. In the North Sea, declining stocks, changes in technical measures, changes in population structure and the establishment of a recovery programme for cod (Gadus morhua) will alter the amount of fish discarded. This region also supports internationally important populations of seabirds, some of which feed extensively, but facultatively, on discards, in particular on undersized haddock (Melanogrammus aeglefinus) and whiting (Merlangius merlangus). Here we use long-term data sets from the northern North Sea to show that there is a direct link between discard availability and discard use by a generalist predator and scavenger--the great skua (Stercorarius skua). Reduced rates of discarding, particularly when coupled with reduced availability of small shoaling pelagic fish such as sandeel (Ammodytes marinus), result in an increase in predation by great skuas on other birds. This switching of prey by a facultative scavenger presents a potentially serious threat to some seabird communities.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. British Ecological Society is collaborating with JSTOR to digitize, preserve and extend access to Journal of Animal Ecology. Summary 1. We develop an individuals-based model that predicts the strength of interference between foraging animals from basic elements of their behaviour. The model is based on the same principles as previous behaviour-based interference models, but extends and adds further realism to these models. One key difference is that in our model the responses of animals to competitors are not fixed, as is assumed in previous models. Instead, animals use optimal decision rules to determine responses which maximize their intake rate. 2. The general shape of interference function generated by the model is similar to that predicted by previous behaviour-based models. Interference is insignificant at low competitor densities, but steadily increases in intensity as density rises. However, comparison with the observed level of interference between oystercatchers, Haematopus ostralegus, feeding on mussels, Mytilus edulis, shows that the model's predictive power is substantially increased through the addition of optimal decision rules. When animals have a fixed response to encounters, too much interference occurs because dominant animals waste time avoiding subdominants and subdominants waste time attempting, but failing, to steal prey from dominants. When animals use optimal decision rules, only subdominants avoid, and only dominants initiate attacks. Interference is therefore reduced and is much closer to that observed. 3. The conditions under which optimal decision rules will lead to interference are described in terms of basic elements of foraging behaviour. Interference is predicted to occur when handling time and the probability of winning fights are high, and when prey encounter rate and the duration of fights are low. These parameters are used to predict successfully the presence or absence of interference in a range of shorebirdprey systems. 4. We suggest that behaviour-based interference models will need to incorporate optimal decision rules if they are to predict accurately the strength of interference observed in real predator-prey systems.Key-words: avoidance behaviour, individuals-based model, interference competition, kleptoparasitism, optimal foraging behaviour.

Summary1. In order to assess the future impact of a proposed development or evaluate the cost eectiveness of proposed mitigating measures, ecologists must be able to provide accurate predictions under new environmental conditions. The diculty with predicting to new circumstances is that often there is no way of knowing whether the empirical relationships upon which models are based will hold under the new conditions, and so predictions are of uncertain accuracy. 2. We present a model, based on the optimality approach of behavioural ecology, that is designed to overcome this problem. The model's central assumption is that each individual within a population always behaves in order to maximize its ®tness. The model follows the optimal decisions of each individual within a population and predicts population mortality rate from the survival consequences of these decisions. Such behaviour-based models should provide a reliable means of predicting to new circumstances because, even if conditions change greatly, the basis of predictions ± ®tness maximization ± will not. 3. The model was parameterized and tested for a shorebird, the oystercatcher Haematopus ostralegus. Development aimed to minimize the dierence between predicted and observed overwinter starvation rates of juveniles, immatures and adults during the model calibration years of 1976±80. The model was tested by comparing its predicted starvation rates with the observed rates for another sample of years during 1980±91, when the oystercatcher population was larger than in the model calibration years. It predicted the observed density-dependent increase in mortality rate in these years, outside the conditions for which it was parameterized. 4. The predicted overwinter mortality rate was based on generally realistic behaviour of oystercatchers within the model population. The two submodels that predicted the interference-free intake rates and the numbers and densities of birds on the dierent mussel Mytilus edulis beds at low water did so with good precision. The model also predicted reasonably well (i) the stage of the winter at which the birds starved; (ii) the relative mass of birds using dierent feeding methods; (iii) the number of minutes birds spent feeding on mussels at low water during both the night and day; and (iv) the dates at which birds supplemented their low tide intake of mussels by also feeding on supplementary prey in ®elds while mussel beds were unavailable over the high water period. 5. A sensitivity analysis showed that the model's predictive ability depended on virtually all of its parameters. However, the importance of dierent parameters varied considerably. In particular, variation in gross energetic parameters had a greater in¯uence on predictions than variations in behavioural parameters. In accord with this, much of the model's predictive power was retained when a detailed foraging submodel was replaced with a simple functional response relating intake rate to Correspondence: R. A. Stillman. CEH Dorset, Winfrith Technology Centre, Winfr...

Summary 1.Behaviour-based models of animal population dynamics provide ecologists with a powerful tool for predicting the response of such populations to both natural and human-induced environmental changes. 2. We developed this approach by addressing two outstanding issues in the application of such models: the need to adopt a large-scale spatially explicit approach, and the need to consider the year-round dynamics of animal populations. 3. Spatially explicit, year-round, behaviour-based models of two populations of arctic-breeding geese, the Svalbard population of the barnacle goose Branta leucopsis and the dark-bellied race of the brent goose Branta bernicla, were developed. Both populations have been the subject of serious conservation concern and are currently a source of increasing con¯ict with agricultural interests. 4. There was generally good agreement between empirically derived and modelgenerated density-dependent functions, and of seasonal patterns of the distribution and movement of populations within and between sites, and of energy reserve levels within a population. 5. Sensitivity analyses, however, highlighted the importance of accurate parameter estimation with respect to the predictions of such models, and the potential¯aws in the predictions of existing models that have not adopted a spatially explicit approach when dealing with wide-ranging migratory populations. 6. The eect of the removal of a given area of habitat on both populations was predicted to vary depending upon the spatial con®guration of the change. This further emphasizes the need for a spatially explicit approach. 7. Both barnacle goose and brent goose populations were predicted to decline following habitat loss in their winter or spring-staging sites. Simulations suggested that barnacle geese might be less vulnerable to winter habitat loss than brent geese. This re¯ected the relative strengths of the density-dependence of productivity and winter mortality in the two models and provided a clear illustration of the need for a year-round approach to animal population dynamics. 8. We believe that these models, and this approach to understanding the population dynamics of long-distance migrants, will be bene®cial in attempting to answer the increasingly urgent and frequent requests to predict the response of such populations to environmental change.